In this Phase II SBIR project, Daniel H. Wagner Associates will develop a full-scale prototype Air Combat Identification (ACID) Module that will improve the accuracy of Track Management or Data Fusion systems when attempting to estimate the identity or classification of an Air target. The underlying technical mechanism by which the ACID module will estimate the targets identity is a Bayesian Network (BN) based on the taxonomy of air targets (Allegiance, Nationality, Category, Type, etc.) and the types of measurements or evidence available for estimating the various attributes that characterize the targets. The evidence includes measurable characteristics of the target such as its radar cross section, length, or shape. It also includes measurements related to the type of emitter, if any, operating aboard the target, as well as intelligence type information from possibly classified sources. Finally, the ACID module will also be able to process any kinematic evidence indicative of the identity of the target, such as maximum speed, geographic origin, or maneuverability (flight performance characteristics).